Application of intelligent grammar error correction system following deep learning algorithm in English teaching
Yang Zhang
Abstract
The purpose is to explore the application of deep learning technology in the English grammar error correction algorithm. An English grammar error correction model based on seq2seq (Sequence to Sequence) is established, and then its ability is improved applied to English teaching. In addition, the advanced edge calculation in recent years is used to improve the training efficiency and error-correction ability of the model. The TensorFlow framework is used to implement the model, which verifies the effectiveness of the error-correction algorithm model and greatly improves the accuracy of the error-correction system. The results show that the application of artificial intelligence in grammar error correction has gradually attracted the attention of relevant researchers. The edge computing model performs better than the seq2seq model in a variety of data types, and the accuracy in spelling error correction is improved by nearly 44.21%.